But to be honest, this liar is a college-educated liar. At least he used convolution, which is a special state of integration, learned in advanced mathematics.

Dr. Ben saw a joke today, saying that there is an awesome trading system that uses CNN convolutional neural network. Are people in the currency circle so easy to deceive? Ask the author if he is just fooling around. CNN convolutional neural network is mainly used for image recognition and simulation of computer vision.

This involves turning data flow into information entropy. If you turn your transaction data into information entropy, you can speculate in coins. Is this nonsense?

Convolutional Neural Network,
CNN) is a deep learning model that has achieved great success in the field of computer vision. Their design is inspired by visual systems in biology and aims to simulate the way humans process vision. In the past few years, CNN has made significant progress in image recognition, object detection, image generation and many other fields, becoming an important part of computer vision and deep learning research.

CNN has a wide range of applications in the field of image processing, including but not limited to:
Image classification: By training a CNN model, images can be automatically classified, such as identifying animals, vehicles, faces, etc.
Object detection: CNN can detect specific objects in images and mark their locations and bounding boxes, such as traffic signs, pedestrians, etc.
Image segmentation: CNN can segment the image into multiple semantic regions, such as different objects or scenes in the image.

Opencv is an open source library for computer vision. The core image recognition library uses the CNN algorithm.

Converting image and video streams into information entropy can be used for image recognition. Can your transaction data be converted into information entropy and used for matching?